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  2. Relevance feedback - Wikipedia

    en.wikipedia.org/wiki/Relevance_feedback

    Relevance feedback is a feature of some information retrieval systems. The idea behind relevance feedback is to take the results that are initially returned from a given query, to gather user feedback, and to use information about whether or not those results are relevant to perform a new query. We can usefully distinguish between three types ...

  3. Wikipedia:Relevance - Wikipedia

    en.wikipedia.org/wiki/Wikipedia:Relevance

    Relevance level "Lower" – Information that is "twice removed" should usually not be included unless the other considerations described above are unusually strong. For example, in the above "John Smith" article, "Murderer Larry Jones was also a member of the XYZ organization."

  4. Wikipedia:Relevance/Review B - Wikipedia

    en.wikipedia.org/wiki/Wikipedia:Relevance/Review_B

    Main page; Contents; Current events; Random article; About Wikipedia; Contact us; Donate

  5. Rocchio algorithm - Wikipedia

    en.wikipedia.org/wiki/Rocchio_algorithm

    The Rocchio algorithm is based on a method of relevance feedback found in information retrieval systems which stemmed from the SMART Information Retrieval System developed between 1960 and 1964. Like many other retrieval systems, the Rocchio algorithm was developed using the vector space model .

  6. However, some statements in the article are biased. Please remember that all articles must be written from a neutral point of view. Here are some tips to help you write unbiased articles." If you regularly respond to requests for feedback here, please consider adding the following userbox to your userpage: {{Wikipedia:Requests for feedback ...

  7. Relevance - Wikipedia

    en.wikipedia.org/wiki/Relevance

    Relevance is the connection between topics that makes one useful for dealing with the other. Relevance is studied in many different fields, including cognitive science, logic, and library and information science. Epistemology studies it in general, and different theories of knowledge have different implications for what is considered relevant.

  8. Query expansion - Wikipedia

    en.wikipedia.org/wiki/Query_expansion

    Pseudo-relevance feedback is efficient in average but can damage results for some queries, [7] especially difficult ones since the top retrieved documents are probably non-relevant. Pseudo-relevant documents are used to find expansion candidate terms that co-occur with many query terms. [ 8 ]

  9. Wikipedia:Relevance/Review A - Wikipedia

    en.wikipedia.org/wiki/Wikipedia:Relevance/Review_A

    2.1 Practical realities of "relevancy" in Wikipedia. 2.2 Guiding principles. 2.2.1 Content must be about the subject of the article.